EAI Endorsed Transactions on Internet of Things https://publications.eai.eu/index.php/IoT <p>EAI Endorsed Transactions on Internet of Things is open access, a peer-reviewed scholarly journal focused on all areas related to the technologies and application fields related to the Internet of Things. The journal publishes research articles, review articles, commentaries, editorials, technical articles, and short communications on a quarterly frequency. Authors are not charged for article submission and processing.</p> en-US <p>This is an open-access article distributed under the terms of the Creative Commons Attribution <a href="https://creativecommons.org/licenses/by/3.0/" target="_blank" rel="noopener">CC BY 3.0</a> license, which permits unlimited use, distribution, and reproduction in any medium so long as the original work is properly cited.</p> publications@eai.eu (EAI Publications Department) publications@eai.eu (EAI Support) Tue, 13 Sep 2022 13:59:01 +0000 OJS http://blogs.law.harvard.edu/tech/rss 60 Use of Neural Topic Models in conjunction with Word Embeddings to extract meaningful topics from short texts https://publications.eai.eu/index.php/IoT/article/view/2263 <p class="ICST-abstracttext"><span lang="EN-GB">Unsupervised machine learning is utilized as a part of the process of topic modeling to discover dormant topics hidden within a large number of documents. The topic model can help with the comprehension, organization, and summarization of large amounts of text. Additionally, it can assist with the discovery of hidden topics that vary across different texts in a corpus. Traditional topic models like pLSA (probabilistic latent semantic analysis) and LDA suffer performance loss when applied to short-text analysis caused by the lack of word co-occurrence information in each short text. One technique being developed to solve this problem is pre-trained word embedding (PWE) with an external corpus used with topic models. These techniques are being developed to perform interpretable topic modeling on short texts. Deep neural networks (DNN) and deep generative models have recently advanced, allowing neural topic models (NTM) to achieve flexibility and efficiency in topic modeling. There have been few studies on neural-topic models with pre-trained word embedding for producing significant topics from short texts. An extensive study with five NTMs was accomplished to test the efficacy of additional PWE in generating comprehensible topics through experiments with different datasets in Arabic and French concerning Moroccan news published on Facebook pages. Several metrics, including topic coherence and topic diversity, are utilized in the process of evaluating the extracted topics. Our research shows that the topic coherence of short texts can be significantly improved using a word embedding with an external corpus.</span></p> Nassera HABBAT, Houda ANOUN, Larbi HASSOUNI, Hicham NOURI Copyright (c) 2022 EAI Endorsed Transactions on Internet of Things https://creativecommons.org/licenses/by/3.0/ https://publications.eai.eu/index.php/IoT/article/view/2263 Fri, 30 Sep 2022 00:00:00 +0000 An Overview of IoT Solutions in Climate Smart Agriculture for Food Security in Sub Saharan Africa: Challenges and Prospects https://publications.eai.eu/index.php/IoT/article/view/2696 <p class="ICST-abstracttext"><span lang="EN-GB">INTRODUCTION: Climate smart agriculture (CSA) which involves the integration of IoT and cloud computing is an emerging agricultural paradigm that is foreseen to be the main driver of agriculture as the 21st century progresses. Sub-Saharan Africa lags in this regard and therefore deserves a special focus.</span></p><p class="ICST-abstracttext"><span lang="EN-GB">OBJECTIVES: This paper presents an overview of Internet-of-Things (IoT) solutions in CSA in the context of food security in sub-Saharan Africa (SSA)</span></p><p class="ICST-abstracttext"><span lang="EN-GB">METHODS: An overview of the status of food insecurity in SSA and associated factors is presented. The paper then focused on IoT as a technology and how it can be used for CSA in SSA through use cases; possible challenges were also examined.</span></p><p class="ICST-abstracttext"><span lang="EN-GB">RESULTS: The paper showed that with CSA, SSA can become a net exporter of food.</span></p><p class="ICST-abstracttext"><span lang="EN-GB">CONCLUSION: The paper concludes with open issues like the funding of research and development which must be addressed if SSA is to leverage IoT technology to attain food security.</span></p> Peter Dibal, Elizabeth Onwuka, Zubair Suleiman, Bala Salihu, Emmanuel Nwankwo, Supreme Okoh Copyright (c) 2022 EAI Endorsed Transactions on Internet of Things https://creativecommons.org/licenses/by/3.0/ https://publications.eai.eu/index.php/IoT/article/view/2696 Tue, 13 Sep 2022 00:00:00 +0000